shape_handle, static_cast<DataType>(types[i]));
  }

  ic->set_output_handle_shapes_and_types(output.index, shape_and_type_vec);
}

// Helpers for loading a TensorFlow plugin (a .so file).
Status LoadDynamicLibrary(const char* library_filename, void** result,
                          const void** buf, size_t* len);

unsigned char TF_GetXlaConstantFoldingDisabled() {
  return static_cast<unsigned char>(
      tensorflow::GetBuildXlaOpsPassFlags()->tf_xla_disable_constant_folding);
}

void TF_SetXlaConstantFoldingDisabled(unsigned char should_enable) {
  tensorflow::GetBuildXlaOpsPassFlags()->tf_xla_disable_constant_folding =
      static_cast<bool>(should_enable);
}

void TF_SetXlaMinClusterSize(int size) {
  tensorflow::MarkForCompilationPassFlags* flags =

  EXPECT_TRUE(second_block);
  // Reading the second full block will return 8 bytes, from a cache hit.
  second_block = false;
  TF_EXPECT_OK(ReadCache(&cache, "", block_size, block_size, &out));
  EXPECT_FALSE(second_block);
  EXPECT_EQ(out.size(), file_size - block_size);
}

TEST(RamFileBlockCacheTest, Inconsistent) {
  // Tests the detection of interrupted reads leading to partially filled blocks

#include "tensorflow/core/framework/function.pb.h"
#include "tensorflow/core/platform/casts.h"
#include "tensorflow/core/platform/env.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/macros.h"
#include "tensorflow/core/platform/protobuf.h"
#include "tensorflow/core/platform/strcat.h"
#include "tensorflow/core/platform/test.h"

#include "tensorflow/core/grappler/costs/op_performance_data.pb.h"
#include "tensorflow/core/grappler/grappler_item.h"
#include "tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/protobuf/rewriter_config.pb.h"
#include "tsl/platform/env.h"
#include "tsl/platform/errors.h"

namespace {

//     but plugins didn't provide will be set to `nullptr` values and core
//     TensorFlow will know to not call these on behalf of users;
//   * increased security as plugins will not be able to alter function table
//     after loading up. Thus, malicious plugins can't alter functionality to
//     probe for gadgets inside core TensorFlow. We can even protect the area
//     of memory where the copies reside to not allow any more writes to it